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Benjamin Sorenson; Kenneth Hanson – Journal of Chemical Education, 2023
In spring 2020, the chemical education community faced an abrupt transition from in-person to online classes, which also necessitated online assessments. Building upon an existing three-semester study (F17, S19, and F19) using Rasch modeling and classical testing theory to improve in-person multiple choice exams, this study investigates the impact…
Descriptors: Undergraduate Study, Chemistry, COVID-19, Pandemics
Josh Freeman – Higher Education Policy Institute, 2024
This new Policy Note by HEPI and Kortext explores students' attitudes to AI. Based on a poll of 1,250 students through UCAS, we build a picture of the way students use and view generative AI technologies like ChatGPT and Google Bard. We find that the use of generative AI has become normalised in higher education, but that universities have so far…
Descriptors: Undergraduate Students, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Xuandong Zhao – ProQuest LLC, 2024
The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…
Descriptors: Computational Linguistics, Intellectual Property, Artificial Intelligence, Productivity
Jiahui Luo – Assessment & Evaluation in Higher Education, 2024
This study offers a critical examination of university policies developed to address recent challenges presented by generative AI (GenAI) to higher education assessment. Drawing on Bacchi's 'What's the problem represented to be' (WPR) framework, we analysed the GenAI policies of 20 world-leading universities to explore what are considered problems…
Descriptors: Artificial Intelligence, Educational Policy, College Students, Student Evaluation
Christophe O. Soulage; Fabien Van Coppenolle; Fitsum Guebre-Egziabher – Advances in Physiology Education, 2024
Artificial intelligence (AI) has gained massive interest with the public release of the conversational AI "ChatGPT," but it also has become a matter of concern for academia as it can easily be misused. We performed a quantitative evaluation of the performance of ChatGPT on a medical physiology university examination. Forty-one answers…
Descriptors: Medical Students, Medical Education, Artificial Intelligence, Computer Software
Kaveh Jalilzadeh; Mojgan Rashtchi; Fatemeh Mirzapour – Language Testing in Asia, 2024
A challenging aspect of online education is assessment since academic integrity could be violated due to students' cheating behaviors. The current qualitative research investigated English teachers' perceptions of why students cheat in online assessments. Besides, it attempted to find strategies to reduce cheating in online assessments. Twelve…
Descriptors: Cheating, Computer Assisted Testing, Coping, English (Second Language)
Usani Joseph Ofem; Valentine Joseph Owan; Mary Arikpo Iyam; Maryrose Ify Udeh; Pauline Mbua Anake; Sylvia Victor Ovat – Education and Information Technologies, 2025
While previous studies have explored students' use of different AI tools for academic purposes, studies that have specifically investigated students' use of ChatGPT for dishonest academic purposes in Nigeria are lacking. The consequence of this contextual and knowledge gap is a lack of specific understanding regarding students' engagement with…
Descriptors: Student Attitudes, Usability, Artificial Intelligence, Technology Uses in Education
Patrik Holm; Ulrik Terp; Christina Fjaeraa Alfredsson – Discover Education, 2025
Academic dishonesty is a growing problem in higher education. This study examines students' attitudes toward cheating. The sample consisted of 318 students enrolled in health science courses at a Swedish university. A survey-based quantitative approach was employed, integrating qualitative responses from open-ended questions. We investigated…
Descriptors: Cheating, Student Attitudes, College Students, Tests
Jonathan M. Golding; Anne Lippert; Jeffrey S. Neuschatz; Ilyssa Salomon; Kelly Burke – Teaching of Psychology, 2025
Background: The advent of generative-artificial intelligence (AI) applications introduces new challenges for colleges. Importantly, the growth of these applications requires faculty to adjust their pedagogy to account for the changing technological landscape. Objective: As colleges wrestle with the implications of these applications, it is…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Humanities
Rasha Mohamed Abdelrahman; Najeh Rajeh Alsalhi; Ahmad Mohammad Alzoubi; Abderrahim Benlahcene; Marei Ahmed; Abdalla Falah El-Mneizel – Educational Process: International Journal, 2025
Background/purpose: This study aims to better understand undergraduate students' perceptions of cheating in online learning programs at Ajman University, one of the higher education institutions in the United Arab Emirates. Materials/methods: The study used a descriptive method, employing a questionnaire instrument to collect data from faculty…
Descriptors: Foreign Countries, Undergraduate Students, Student Attitudes, Cheating
Lebohang Victoria Mulaudzi; Joleen Hamilton – Journal of Academic Ethics, 2025
This qualitative study explores lecturers' perspectives on the role of artificial intelligence (AI) in personalised learning within higher education. The rapid proliferation of AI has introduced numerous ethical challenges, including the potential for academic dishonesty and misuse. One concern highlighted in this study is maintaining academic…
Descriptors: College Faculty, Teacher Attitudes, Artificial Intelligence, Technology Uses in Education
Hassan Hessari; Ankit Agarwalla; Mohammad Bai; Morteza Vahedian; Ali Bai – International Journal on E-Learning, 2025
This study investigates the multifaceted impact of generative AI tools (e.g., ChatGPT, Gemini) on higher education. Employing grounded theory, we analyzed the experiences of eight students using these tools in their academic work. Our findings reveal both significant benefits, including enhanced learning, efficiency, and accessibility, and…
Descriptors: Artificial Intelligence, Technology Uses in Education, College Students, Learning Processes
Miron, Jennie; McKenzie, Amanda; Eaton, Sarah Elaine; Stoesz, Brenda; Thacker, Emma; Devereaux, Lisa; Persaud, Nira; Steeves, Marcia; Rowbotham, Kate – Canadian Journal of Educational Administration and Policy, 2021
In this article we report findings from a review of universities' academic integrity policies in Ontario, Canada. The research team systematically extracted, reviewed, and evaluated information from policy documents in an effort to understand how these documents described contract cheating in Ontario universities (n = 21). In all, 23 policies were…
Descriptors: Integrity, Ethics, Cheating, Outsourcing
Makridis, Odysseus; Englander, Fred – Journal of Academic Ethics, 2021
This paper considers characteristic views advanced in the past fifteen years that may be considered relatively sympathetic to student practices of cheating on graded assignments or exams. We detect and analyze typical fallacies that are recurrent in articles that promote a revisionist view of cheating as morally permissible. We offer a general,…
Descriptors: Cheating, Ethics, Tests, Assignments
Ashford, Theresa – Journal of Academic Ethics, 2021
Academic integrity (AI) is a complex problem that challenges how we view action, intentions, research, and knowledge production as human agents working with computers. This paper proposes that a productive approach to support AI is found at the nexus of behavioural ethics and a view of hybrid app-human agency. The proposal brings together AI…
Descriptors: Integrity, Cheating, Plagiarism, Technology Uses in Education

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